A data-driven model of biomarker changes in sporadic Alzheimer's disease.

We demonstrate the use of a probabilistic generative model to explore the biomarker changes occurring as Alzheimer's disease develops and progresses. We enhanced the recently introduced event-based model for use with a multi-modal sporadic disease data set. This allows us to determine the sequence in which Alzheimer's disease biomarkers become abnormal without reliance on a priori clinical diagnostic information or explicit biomarker cut points. The model also characterizes the uncertainty in the ordering and provides a natural patient staging system. Two hundred and eighty-five subjects (92 cognitively normal, 129 mild cognitive impairment, 64 Alzheimer's disease) were selected from the Alzheimer's Disease Neuroimaging Initiative with measurements of 14 Alzheimer's disease-related biomarkers including cerebrospinal fluid proteins, regional magnetic resonance imaging brain volume and rates of atrophy measures, and cognitive test scores. We used the event-based model to determine the sequence of biomarker abnormality and its uncertainty in various population subgroups. We used patient stages assigned by the event-based model to discriminate cognitively normal subjects from those with Alzheimer's disease, and predict conversion from mild cognitive impairment to Alzheimer's disease and cognitively normal to mild cognitive impairment. The model predicts that cerebrospinal fluid levels become abnormal first, followed by rates of atrophy, then cognitive test scores, and finally regional brain volumes. In amyloid-positive (cerebrospinal fluid amyloid-β1-42 < 192 pg/ml) or APOE-positive (one or more APOE4 alleles) subjects, the model predicts with high confidence that the cerebrospinal fluid biomarkers become abnormal in a distinct sequence: amyloid-β1-42, phosphorylated tau, total tau. However, in the broader population total tau and phosphorylated tau are found to be earlier cerebrospinal fluid markers than amyloid-β1-42, albeit with more uncertainty. The model's staging system strongly separates cognitively normal and Alzheimer's disease subjects (maximum classification accuracy of 99%), and predicts conversion from mild cognitive impairment to Alzheimer's disease (maximum balanced accuracy of 77% over 3 years), and from cognitively normal to mild cognitive impairment (maximum balanced accuracy of 76% over 5 years). By fitting Cox proportional hazards models, we find that baseline model stage is a significant risk factor for conversion from both mild cognitive impairment to Alzheimer's disease (P = 2.06 × 10(-7)) and cognitively normal to mild cognitive impairment (P = 0.033). The data-driven model we describe supports hypothetical models of biomarker ordering in amyloid-positive and APOE-positive subjects, but suggests that biomarker ordering in the wider population may diverge from this sequence. The model provides useful disease staging information across the full spectrum of disease progression, from cognitively normal to mild cognitive impairment to Alzheimer's disease. This approach has broad application across neurodegenerative disease, providing insights into disease biology, as well as staging and prognostication.

Young AL ，Oxtoby NP ，Daga P ，Cash DM ，Fox NC ，Ourselin S ，Schott JM ，Alexander DC ，Alzheimer’s Disease Neuroimaging Initiative ... -  《-》

Alzheimer's disease cerebrospinal fluid biomarker in cognitively normal subjects.

In a large multicentre sample of cognitively normal subjects, as a function of age, gender and APOE genotype, we studied the frequency of abnormal cerebrospinal fluid levels of Alzheimer's disease biomarkers including: total tau, phosphorylated tau and amyloid-β1-42. Fifteen cohorts from 12 different centres with either enzyme-linked immunosorbent assays or Luminex® measurements were selected for this study. Each centre sent nine new cerebrospinal fluid aliquots that were used to measure total tau, phosphorylated tau and amyloid-β1-42 in the Gothenburg laboratory. Seven centres showed a high correlation with the new Gothenburg measurements; therefore, 10 cohorts from these centres are included in the analyses here (1233 healthy control subjects, 40-84 years old). Amyloid-β amyloid status (negative or positive) and neurodegeneration status (negative or positive) was established based on the pathological cerebrospinal fluid Alzheimer's disease cut-off values for cerebrospinal fluid amyloid-β1-42 and total tau, respectively. While gender did not affect these biomarker values, APOE genotype modified the age-associated changes in cerebrospinal fluid biomarkers such that APOE ε4 carriers showed stronger age-related changes in cerebrospinal fluid phosphorylated tau, total tau and amyloid-β1-42 values and APOE ε2 carriers showed the opposite effect. At 40 years of age, 76% of the subjects were classified as amyloid negative, neurodegeneration negative and their frequency decreased to 32% at 85 years. The amyloid-positive neurodegeneration-negative group remained stable. The amyloid-negative neurodegeneration-positive group frequency increased slowly from 1% at 44 years to 16% at 85 years, but its frequency was not affected by APOE genotype. The amyloid-positive neurodegeneration-positive frequency increased from 1% at 53 years to 28% at 85 years. Abnormally low cerebrospinal fluid amyloid-β1-42 levels were already frequent in midlife and APOE genotype strongly affects the levels of cerebrospinal fluid amyloid-β1-42, phosphorylated tau and total tau across the lifespan without influencing the frequency of subjects with suspected non-amyloid pathology.

Toledo JB ，Zetterberg H ，van Harten AC ，Glodzik L ，Martinez-Lage P ，Bocchio-Chiavetto L ，Rami L ，Hansson O ，Sperling R ，Engelborghs S ，Osorio RS ，Vanderstichele H ，Vandijck M ，Hampel H ，Teipl S ，Moghekar A ，Albert M ，Hu WT ，Monge Argilés JA ，Gorostidi A ，Teunissen CE ，De Deyn PP ，Hyman BT ，Molinuevo JL ，Frisoni GB ，Linazasoro G ，de Leon MJ ，van der Flier WM ，Scheltens P ，Blennow K ，Shaw LM ，Trojanowski JQ ，Alzheimer’s Disease Neuroimaging Initiative ... -  《-》

Is cerebral microbleed prevalence relevant as a biomarker in amnestic mild cognitive impairment and mild Alzheimer's disease?

Rabelo AG ，Teixeira CV ，Magalhães TN ，Carletti-Cassani AFM ，Amato Filho AC ，Joaquim HP ，Talib LL ，Forlenza O ，Ribeiro PA ，Secolin R ，Lopes-Cendes I ，Cendes F ，Balthazar ML ... -  《-》

Cognitive Variability Predicts Incident Alzheimer's Disease and Mild Cognitive Impairment Comparable to a Cerebrospinal Fluid Biomarker.

Gleason CE ，Norton D ，Anderson ED ，Wahoske M ，Washington DT ，Umucu E ，Koscik RL ，Dowling NM ，Johnson SC ，Carlsson CM ，Asthana S ，Alzheimer’s Disease Neuroimaging Initiative ... -  《-》

Utility of an Alzheimer's Disease Risk-Weighted Polygenic Risk Score for Predicting Rates of Cognitive Decline in Preclinical Alzheimer's Disease: A Prospective Longitudinal Study.

Porter T ，Burnham SC ，Milicic L ，Savage G ，Maruff P ，Lim YY ，Li QX ，Ames D ，Masters CL ，Rainey-Smith S ，Rowe CC ，Salvado O ，Groth D ，Verdile G ，Villemagne VL ，Laws SM ，AIBL Research Group ... -  《-》